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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Improved crystallographic models through iterated local density-guided model deformation and reciprocal-space refinement

A density-based procedure is described for improving a homology model that is locally accurate but differs globally. The model is deformed to match the map and refined, yielding an improved starting point for density modification and further model-building. An approach is presented for addressing the challenge of model rebuilding after molecular replacement in cases where the placed template is very different from the structure to be determined. The approach takes advantage of the observation that a template and target structure may have local structures that can be superimposed much more closely than can their complete structures. A density-guided procedure for deformation of a properly placed template is introduced. A shift in the coordinates of each residue in the structure is calculated based on optimizing the match of model density within a 6 Å radius of the center of that residue with a prime-and-switch electron-density map. The shifts are smoothed and applied to the atoms in each residue, leading to local deformation of the template that improves the match of map and model. The model is then refined to improve the geometry and the fit of model to the structure-factor data. A new map is then calculated and the process is repeated until convergence. The procedure can extend the routine applicability of automated molecular replacement, model building and refinement to search models with over 2 Å r.m.s.d. representing 65–100% of the structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Biophysical drivers of seasonal variability in Sphagnum gross primary production in a northern temperate bog

Sphagnum mosses are the keystone species of peatland ecosystems. With rapid rates of climate change occurring in high latitudes, vast reservoirs of carbon accumulated over millennia in peatland ecosystems are potentially vulnerable to rising temperature and changing precipitation. We investigate the seasonal drivers of Sphagnum gross primary production (GPP)—the entry point of carbon into wetland ecosystems. Continuous flux measurements and flux partitioning show a seasonal cycle of Sphagnum GPP that peaked in the late summer, well after the peak in photosynthetically active radiation. Wavelet analysis showed that water table height was the key driver of weekly variation in Sphagnum GPP in the early summer and that temperature was the primary driver of GPP in the late summer and autumn. Flux partitioning and a process-based model of Sphagnum photosynthesis demonstrated the likelihood of seasonally dynamic maximum rates of photosynthesis and a logistic relationship between the water table and photosynthesizing tissue area when the water table was at the Sphagnum surface. Here, the model also suggested that variability in internal resistance to CO 2 transport, a function of Sphagnum water content, had minimal effect on GPP. To accurately model Sphagnum GPP, we recommend the following: (1) understanding seasonal photosynthetic trait variation and its triggers in Sphagnum ; (2) characterizing the interaction of Sphagnum photosynthesizing tissue area with water table height; (3) modeling Sphagnum as a “soil” layer for consistent simulation of water dynamics; and (4) measurement of Sphagnum “canopy” properties: extinction coefficient (k), clumping (Ω), and maximum stem area index (SAI).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Specialized proteomic responses and an ancient photoprotection mechanism sustain marine green algal growth during phosphate limitation

Marine algae perform approximately half of global carbon fixation, but their growth is often limited by availability of phosphate or other nutrients1,2. As oceans warm, the area of phosphate-limited surface waters is predicted to increase, resulting in ocean desertification3,4. Understanding the responses of key eukaryotic phytoplankton to nutrient limitation is therefore critical5,6. We used advanced photo-bioreactors to investigate how the widespread green alga Micromonas commoda grows under transitions from replete nutrients to chronic phosphate limitation and subsequent relief, analyzing photosystem changes and broad cellular responses using proteomics, transcriptomics and biophysical measurements. We find that physiological and protein expression responses previously attributed to stress are critical to supporting stable exponential growth when phosphate is limiting. Unexpectedly, the abundance of most proteins involved in light-harvesting does not change, but an ancient light-harvesting related protein, LHCSR, is induced and dissipates damaging excess absorbed light as heat during P-limitation. Concurrently, a suite of uncharacterized proteins with narrow phylogenetic distributions increase multifold. Notably, of the proteins that exhibit significant changes, 70% are not differentially expressed at the mRNA transcript level, highlighting the importance of post-transcriptional processes in microbial eukaryotes. Nevertheless, transcript-protein pairs with concordant changes were identified that will enable more robust interpretation of eukaryotic phytoplankton responses in the field from metatranscriptomic studies. Our results show P-limited Micromonas responds quickly to a fresh pulse of phosphate by rapidly increasing replication and that the protein network associated with this ability is composed of both conserved and phylogenetically recent proteome systems that promote dynamic phosphate homeostasis. That an ancient mechanism for mitigating light-stress is central to sustaining growth throughout extended periods of phosphate limitation highlights possible interactive effects, arising from multiple stressors under ocean change, which could reduce the efficacy of algal strategies for optimizing marine photosynthesis.

marine algae, phosphate, proteomics, ocean warming↗
DOE OSTI2014

MCTP system model based on linear programming optimization of apertures obtained from sequencing patient image data maps

Purpose: The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. Methods: The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called “biophysical” map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Results: Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast irradiation case (Case II) solved with photon and electron modulated beams (IMRT + MERT); and a prostatic bed case (Case III) with a pronounced concave-shaped PTV by using volumetric modulated arc therapy. In the three cases, the required target prescription doses and constraints on organs at risk were fulfilled in a short enough time to allow routine clinical implementation. The quality assurance protocol followed to check CARMEN system showed a high agreement with the experimental measurements. Conclusions: A Monte Carlo treatment planning model exclusively based on maps performed from patient imaging data has been presented. The sequencing of these maps allows obtaining deliverable apertures which are weighted for modulation under a linear programming formulation. The model is able to solve complex radiotherapy treatments with high accuracy in an efficient computation time.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Advances in Understanding Carboxysome Assembly in Prochlorococcus and Synechococcus Implicate CsoS2 as a Critical Component

The marine Synechococcus and Prochlorococcus are the numerically dominant cyanobacteria in the ocean and important in global carbon fixation. They have evolved a CO2-concentrating-mechanism, of which the central component is the carboxysome, a self-assembling proteinaceous organelle. Two types of carboxysome, α and β, encapsulating form IA and form IB D-ribulose-1,5-bisphosphate carboxylase/oxygenase, respectively, differ in gene organization and associated proteins. In contrast to the β-carboxysome, the assembly process of the α-carboxysome is enigmatic. Moreover, an absolutely conserved α-carboxysome protein, CsoS2, is of unknown function and has proven recalcitrant to crystallization. Here, we present studies on the CsoS2 protein in three model organisms and show that CsoS2 is vital for α-carboxysome biogenesis. The primary structure of CsoS2 appears tripartite, composed of an N-terminal, middle (M)-, and C-terminal region. Repetitive motifs can be identified in the N- and M-regions. Multiple lines of evidence suggest CsoS2 is highly flexible, possibly an intrinsically disordered protein. Based on our results from bioinformatic, biophysical, genetic and biochemical approaches, including peptide array scanning for protein-protein interactions, we propose a model for CsoS2 function and its spatial location in the α-carboxysome. Analogies between the pathway for β-carboxysome biogenesis and our model for α-carboxysome assembly are discussed.

assembly↗
DOE OSTI2017

Three-Dimensional Geometry of Collagenous Tissues by Second Harmonic Polarimetry

Collagen is a biological macromolecule capable of second harmonic generation, allowing label-free detection in tissues; in addition, molecular orientation can be determined from the polarization dependence of the second harmonic signal. Previously we reported that in-plane orientation of collagen fibrils could be determined by modulating the polarization angle of the laser during scanning. We have now extended this method so that out-of-plane orientation angles can be determined at the same time, allowing visualization of the 3-dimensional structure of collagenous tissues. This approach offers advantages compared with other methods for determining out-of-plane orientation. First, the orientation angles are directly calculated from the polarimetry data obtained in a single scan, while other reported methods require data from multiple scans, use of iterative optimization methods, application of fitting algorithms, or extensive post-optical processing. Second, our method does not require highly specialized instrumentation, and thus can be adapted for use in almost any nonlinear optical microscopy setup. It is suitable for both basic and clinical applications. We present three-dimensional images of structurally complex collagenous tissues that illustrate the power of such 3-dimensional analyses to reveal the architecture of biological structures.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2004

Forest Attributes from Radar Interferometric Structure and its Fusion with Optical Remote Sensing

The possibility of global, three-dimensional remote sensing of forest structure with interferometric synthetic aperture radar (InSAR) bears on important forest ecological processes, particularly the carbon cycle. InSAR supplements two-dimensional remote sensing with information in the vertical dimension. Its strengths in potential for global coverage complement those of lidar (light detecting and ranging), which has the potential for high-accuracy vertical profiles over small areas. InSAR derives its sensitivity to forest vertical structure from the differences in signals received by two, spatially separate radar receivers. Estimation of parameters describing vertical structure requires multiple-polarization, multiple-frequency, or multiple-baseline InSAR. Combining InSAR with complementary remote sensing techniques, such as hyperspectral optical imaging and lidar, can enhance vertical-structure estimates and consequent biophysical quantities of importance to ecologists, such as biomass. Future InSAR experiments will supplement recent airborne and spaceborne demonstrations, and together with inputs from ecologists regarding structure, they will suggest designs for future spaceborne strategies for measuring global vegetation structure.

InSAR↗
DOE OSTI2021

Comparison of the Forward and Reverse Photocycle Dynamics of Two Highly Similar Canonical Red/Green Cyanobacteriochromes Reveals Unexpected Differences

Cyanobacteriochromes (CBCRs) are cyanobacterial photoreceptors that exhibit photochromism between two states: a thermally stable dark-adapted state and a metastable light-adapted state with bound linear tetrapyrrole (bilin) chromophores possessing 15Z and 15E configurations, respectively. The photodynamics of canonical red/green CBCRs have been extensively studied; however, the time scales of their excited-state lifetimes and subsequent ground-state evolution rates widely differ and, at present, remain difficult to predict. Here, we compare the photodynamics of two closely related red/green CBCRs that have substantial sequence identity (~68%) and similar chromophore environments: AnPixJg2 from Anabaena sp. PCC 7120 and NpR6012g4 from Nostoc punctiforme. Using broadband transient absorption spectroscopy on the primary (125 fs to 7 ns) and secondary (7 ns to 10 ms) time scales together with global analysis modeling, our studies revealed that AnPixJg2 and NpR6012g4 have comparable quantum yields for initiating the forward ( 15Z P r → 15E P g ) and reverse ( 15E P g → 15Z P r ) reactions, which proceed through monotonic and nonmonotonic mechanisms, respectively. In addition to small discrepancies in the kinetics, the secondary reverse dynamics resolved unique features for each domain: intermediate shunts in NpR6012g4 and a Meta-Gf intermediate red-shifted from the 15Z P r photoproduct in AnPixJg2. Altogether, this study supports the conclusion that sequence similarity is a useful criterion for predicting pathways of the light-induced evolution and quantum yield of generating primary intermediate Φ p within subfamilies of CBCRs, but more studies are still needed to develop a comprehensive molecular level understanding of these processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Intermediate-state-trapped mutants pinpoint G protein-coupled receptor conformational allostery

Understanding the roles of intermediate states in signaling is pivotal to unraveling the activation processes of G protein-coupled receptors (GPCRs). However, the field is still struggling to define these conformational states with sufficient resolution to study their individual functions. Here, we demonstrate the feasibility of enriching the populations of discrete states via conformation-biased mutants. These mutants adopt distinct distributions among five states that lie along the activation pathway of adenosine A 2A receptor (A 2A R), a class A GPCR. Our study reveals a structurally conserved cation-π lock between transmembrane helix VI (TM6) and Helix8 that regulates cytoplasmic cavity opening as a “gatekeeper” for G protein penetration. A GPCR activation process based on the well-discerned conformational states is thus proposed, allosterically micro-modulated by the cation-π lock and a previously well-defined ionic interaction between TM3 and TM6. Intermediate-state-trapped mutants will also provide useful information in relation to receptor-G protein signal transduction.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

Wall extensibility: its nature, measurement and relationship to plant cell growth

Expansive growth of plant cells is controlled principally by processes that loosen the wall and enable it to expand irreversibly. The central role of wall relaxation for cell expansion is reviewed. The most common methods for assessing the extension properties of plant cell walls ( wall extensibility') are described, categorized and assessed critically. What emerges are three fundamentally different approaches which test growing cells for their ability (a) to enlarge at different values of turgor, (b) to induce wall relaxation, and (c) to deform elastically or plastically in response to an applied tensile force. Analogous methods with isolated walls are similarly reviewed. The results of these different assays are related to the nature of plant cell growth and pertinent biophysical theory. I argue that the extensibilities' measured by these assays are fundamentally different from one another and that some are more pertinent to growth than others.

Review, Academic↗
DOE OSTI2021

Semi-automated Design of Artificial Intelligence Earth Systems Models

Prediction and observation of water cycles at various scales involve not only patterns isolated in space and time, but also modeling of complex spatio-temporal relationships across multiple domains. For instance, evapotranspiration (ET) and leaf area indexes (LAI) are two parameters that are needed to accurately model and understand land-atmosphere processes. Accurate assessments of ET and LAI are critical for understanding hydrological processes, deforestation, crop yield, and irrigation impacts. However, ET estimates for global simulations are available at very coarse spatial resolution. They are usually derived from satellite data based on broad plant functional types (PFTs), which fail to capture fine-scale variations because of changes in vegetation type across the globe. Similarly LAI estimates have typically been derived from vegetation indices at global scales or estimated locally using physical models, both of which suffer from a range of uncertainties that impact model sensitivity. The new era of AI model development for Earth systems (ES) calls for data-driven methods that provide domain scientists with uncertainty-aware estimations of biophysical parameters such as ET and LAI in a generalizable, interpretable, and discoverable manner.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

2022 American Conference on Neutron Scattering (ACNS 2022)

The 11th American Conference on Neutron Scattering (ACNS 2022) will be held on June 5-9, 2022, in Boulder, CO. The Conference will provide essential information on the breadth and depth of current neutron-related research worldwide. Hosted by the Neutron Scattering Society of America, this year’s Conference will feature a combination of invited and contributed talks, poster sessions, and tutorials. Topics of the conference are: Advances in Neutron Facilities, Instrumentation and Software: Developments in sources, instrumentation, sample environments and control software. Hard Condensed Matter: Magnetism, correlated metals, quantum/topological materials, superconductors, ferroelectrics, multiferroics, glasses, and disorder phenomena. Submissions outlining examples of neutron scattering in industrial and engineering applications involving hard condensed matter systems are also encouraged. Soft Matter: Neutron studies of soft materials and related fields including in situ and in operando studies. Polymers, surfactants, emulsions, gels, nanoparticles, colloidal suspensions and more. Submissions of computational studies or applications of machine learning beneficial to neutron scattering experiments, as well as examples of neutron scattering in industrial and engineering applications are strongly encouraged. Biology, Biophysics and Biotechnology: Neutron studies of biological and biologically relevant systems. Proteins, bio membranes, biological assemblies, natural materials, nucleic acids, drug-delivery platforms and biomedical systems. Submissions of computational studies or applications of machine learning beneficial to biological neutron scattering experiments, as well as examples of neutron scattering in applied research involving biological systems, are strongly encouraged. Materials Chemistry and Energy: Neutron-based studies of functional materials and materials for energy applications. Examples include porous materials such as metal organic frameworks (MOFs), zeolites; phosphors; novel pigments; electrolytes; catalysts; ionic conductors/cathode materials; photovoltaic materials (hybrid perovskites); thermoelectrics; magnetocalorics/electrocalorics. Structural Materials and Engineering: Neutron scattering studies of materials and engineering processes including structural materials, concrete and metals, as well as engineering processes including combustion, corrosion, additive manufacturing, and others. Neutron Physics: Fundamental physical studies of the neutron and related areas. Emerging Applications in Neutron Scattering: Machine Learning and Data Science: Advances in computing power have contributed to rapidly evolving machine learning and data science fields that can be leveraged to the benefit of the neutron scattering community. The purpose of this session is to highlight recent advances in machine learning and data science and to serve as the foundation of a parallel data and computation track highlighting computation advances and applications in neutron scattering throughout the conference.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Using landscape typologies to model socioecological systems: Application to agriculture of the United States Gulf Coast

Agricultural enterprises are vulnerable to the effects of climate variability and change. Improved understanding of the determinants of vulnerability and adaptive capacity in agricultural systems is important for projecting and managing future climate risk. At present, three analytical tools dominate methodological approaches to understanding agroecological vulnerability to climate: process-based crop models, empirical crop models, and integrated assessment models. A common weakness of these approaches is their limited treatment of socio-economic conditions and human agency in modeling agroecological processes and outcomes. This study proposes a framework that uses spatial cluster analysis to generate regional socioecological typologies that capture geographic variance in regional agricultural production and enable attribution of that variance to climatic, topographic, edaphic, and socioeconomic components. This framework was applied to historical corn production (1986-2010) in the U.S. Gulf of Mexico region as a testbed. The results demonstrate that regional socioeconomic heterogeneity is an important driving force in human dominated ecosystems, which we hypothesize, is a function of the link between socioeconomic conditions and the adaptive capacity of agricultural systems. Meaningful representation of future agricultural responses to climate variability and change is contingent upon understanding interactions among biophysical conditions, socioeconomic conditions, and human agency their incorporation in predictive models.

58 GEOSCIENCES↗
DOE OSTI2015

A Potent, Selective, and Cell-Active Inhibitor of Human Type I Protein Arginine Methyltransferases

Protein arginine methyltransferases (PRMTs) play a crucial role in a variety of biological processes. Overexpression of PRMTs has been implicated in various human diseases including cancer. Consequently, selective small-molecule inhibitors of PRMTs have been pursued by both academia and the pharmaceutical industry as chemical tools for testing biological and therapeutic hypotheses. PRMTs are divided into three categories: type I PRMTs which catalyze mono- and asymmetric dimethylation of arginine residues, type II PRMTs which catalyze mono- and symmetric dimethylation of arginine residues, and type III PRMT which catalyzes only monomethylation of arginine residues. Here, we report the discovery of a potent, selective, and cell-active inhibitor of human type I PRMTs, MS023, and characterization of this inhibitor in a battery of biochemical, biophysical, and cellular assays. MS023 displayed high potency for type I PRMTs including PRMT1, -3, -4, -6, and -8 but was completely inactive against type II and type III PRMTs, protein lysine methyltransferases and DNA methyltransferases. A crystal structure of PRMT6 in complex with MS023 revealed that MS023 binds the substrate binding site. MS023 potently decreased cellular levels of histone arginine asymmetric dimethylation. It also reduced global levels of arginine asymmetric dimethylation and concurrently increased levels of arginine monomethylation and symmetric dimethylation in cells. We also developed MS094, a close analog of MS023, which was inactive in biochemical and cellular assays, as a negative control for chemical biology studies. In conclusion, MS023 and MS094 are useful chemical tools for investigating the role of type I PRMTs in health and disease.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Design and applications of a clamp for Green Fluorescent Protein with picomolar affinity

Green fluorescent protein (GFP) fusions are pervasively used to study structures and processes. Specific GFP-binders are thus of great utility for detection, immobilization or manipulation of GFP-fused molecules. We determined structures of two designed ankyrin repeat proteins (DARPins), complexed with GFP, which revealed different but overlapping epitopes. Here in this paper we show a structure-guided design strategy that, by truncation and computational reengineering, led to a stable construct where both can bind simultaneously: by linkage of the two binders, fusion constructs were obtained that “wrap around” GFP, have very high affinities of about 10–30 pM, and extremely slow off-rates. They can be natively produced in E. coli in very large amounts, and show excellent biophysical properties. Their very high stability and affinity, facile site-directed functionalization at introduced unique lysines or cysteines facilitate many applications. As examples, we present them as tight yet reversible immobilization reagents for surface plasmon resonance, as fluorescently labelled monomeric detection reagents in flow cytometry, as pull-down ligands to selectively enrich GFP fusion proteins from cell extracts, and as affinity column ligands for inexpensive large-scale protein purification. We have thus described a general design strategy to create a “clamp” from two different high-affinity repeat proteins, even if their epitopes overlap.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Multispectral satellite observations for arid land studies

Multispectral satellite data when properly calibrated and standardized can be used synergistically for a quantitative analysis of processes and surface characteristics, and for quantifying land surface change. Relationships among multispectral satellite data (visible reflectance, surface temperature and polarization difference of microwave emission at 37 GHz frequency) have been used to develop hypotheses concerning the relative sensitivity of these data to varied land surface characteristics, which needs to be verified by field observations. Radiative transfer models have also been developed to understand these multispectral data. Interannual variations of visible reflectance and polarization difference for the period 1982-1986 over the Sahel and the Sudan zones of Africa show a lagged response with respect to the rainfall deficit during recovery from drought, which needs to be understood in terms of biophysical parameters.

Choudhury, Bhaskar J.↗
NASA NTRS1994

Space observations for global and regional studies of the biosphere

The capability to make space-based measurements of Earth at high spatial and temporal resolutions, which would not otherwise be economically or practically feasible, became available just in time to contribute to scientific understanding of the interactive processes governing the total Earth system. Such understanding has now become essential in order to take practical steps which would counteract or mitigate the pervasive impact of the growing human population on the future habitability of the Earth. The paper reviews the rationale for using space observations for studies of climate and terrestrial ecosystems at global and regional scales, as well as the requirements for such observations for studies of climate and ecosystem dynamics. The present status of these developments is reported along with initiatives under way to advance the use of satellite observations for Earth system studies. The most important contribution of space observations is the provision of physical or biophysical parameters for models representing various components of the Earth system. Examples of such parameters are given for climatic and ecosystem studies.

Cihlar, J.↗